On Feature Selection for Speaker Verification

This paper describes an HMM based speaker verification system, which verifies speakers in their own specific feature space. This ‘individual’ feature space is determined by a Dynamic Programming (DP) feature selection algorithm. A suitable criterion, correlated with Equal Error Rate (EER) was developed and is used for this feature selection algorithm. The algorithm was evaluated on a text-dependent database. A significant improvement in verification results was demonstrated with the DP selected individual feature space. An EER of 4.8% was achieved when the feature set was the “almost standard” Mel Frequency Cepstrum Coefficients (MFCC) space (12 MFCC + 12 ∆MFCC). Under the same conditions, a system based on the selected feature space yielded an EER of only 2.7%.